1. Field of the Invention
The present invention relates generally to an image recognition method and an image recognition system; especially, the present invention relates to a method and a system which can automatically recognize, analyze, and measure ultrasound images, wherein the ultrasound images include fetal ultrasound images; particularly, the present invention relates to an image recognition, analysis, measuring method and a system which can analyze the image, increase recognition efficiency, and automatically conduct the measurement.
2. Description of the Prior Art
Ultrasound detection has advantages of real-time, low cost, easy use, and non-invasion and is widely applied in biomedicine field, particularly to detect the fetal growth in the uterus. Generally, doctors utilize an ultrasound detector detecting ultrasound dynamic images of fetus and try to retrieve the real-time image from best angle. In practical applications, the ultrasound detector has an image recognition system, wherein the image recognition system can read contents of the retrieved real-time image and provide a plurality of image analysis tools. However, the image analysis tools need to be operated manually by users to interpret the contents of the images and to manually measure the contents of the images.
For instance, doctors need to search target images with naked eyes, wherein the target images include a skull image, a femur image, or other organ images. It is noted that the search result of the visual method is easy to generate inaccuracy and inconsistency when the target image is too fuzzy, so that the doctor is hard to determine the correct position of the target image, further influencing the determined result of the target image.
In addition, the doctor drags a scale tool to manually measure a length of the target image when the target image is processed by the image analysis tool. It is noted that measurement conducted by manually dragging the scale tool is subjective, inconsistent, time-consuming and cannot effectively provide a better medical quality. In addition, if the determined result of the target image generates large error, the subsequent dimension measurement will be influenced. For the above reasons, the conventional image cognition system still has many defects.